Melnyk Oleksiy, Ismail Ahmed, Ghorashi Nima S, Heekin Mary, Javan Ramin
Department of Radiology, George Washington University School of Medicine and Health Sciences, Washington D.C., USA.
Cureus. 2023 Dec 4;15(12):e49890. doi: 10.7759/cureus.49890. eCollection 2023 Dec.
Generative artificial intelligence (AI) is rapidly transforming the medical field, as advanced tools powered by large language models (LLMs) make their way into clinical practice, research, and education. Chatbots, which can generate human-like responses, have gained attention for their potential applications. Therefore, familiarity with LLMs and other promising generative AI tools is crucial to harness their potential safely and effectively. As these AI-based technologies continue to evolve, medical professionals must develop a strong understanding of AI terminologies and concepts, particularly generative AI, to effectively tackle real-world challenges and create solutions. This knowledge will enable healthcare professionals to utilize AI-driven innovations for improved patient care and increased productivity in the future. In this brief technical report, we explore 20 of the most relevant terminology associated with the underlying technology behind LLMs and generative AI as they relate to the medical field and provide some examples of how these topics relate to healthcare applications to help in their understanding.
生成式人工智能（AI）正在迅速改变医学领域，随着由大语言模型（LLM）驱动的先进工具进入临床实践、研究和教育领域。能够生成类人回复的聊天机器人因其潜在应用而受到关注。因此，熟悉大语言模型和其他有前景的生成式人工智能工具对于安全有效地利用它们的潜力至关重要。随着这些基于人工智能的技术不断发展，医学专业人员必须深入理解人工智能术语和概念，尤其是生成式人工智能，以便有效应对现实世界的挑战并创造解决方案。这些知识将使医疗保健专业人员能够利用人工智能驱动的创新在未来改善患者护理并提高生产力。在这份简短的技术报告中，我们探讨了与大语言模型和生成式人工智能背后的基础技术相关的20个最相关术语，这些术语与医学领域相关，并提供了一些这些主题与医疗保健应用相关的示例，以帮助理解。
